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#cognitive-computing News & Analysis

8 articles tagged with #cognitive-computing. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

8 articles
AIBullisharXiv – CS AI · Mar 267/10
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Bottlenecked Transformers: Periodic KV Cache Consolidation for Generalised Reasoning

Researchers introduce Bottlenecked Transformers, a new architecture that improves AI reasoning by up to 6.6 percentage points through periodic memory consolidation inspired by brain processes. The system uses a Cache Processor to rewrite key-value cache entries at reasoning step boundaries, achieving better performance on math reasoning benchmarks compared to standard Transformers.

AIBullisharXiv – CS AI · Mar 177/10
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D-MEM: Dopamine-Gated Agentic Memory via Reward Prediction Error Routing

Researchers introduce D-MEM, a biologically-inspired memory architecture for AI agents that uses dopamine-like reward prediction error routing to dramatically reduce computational costs. The system reduces token consumption by over 80% and eliminates quadratic scaling bottlenecks by selectively processing only high-importance information through cognitive restructuring.

AIBullisharXiv – CS AI · Apr 76/10
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SuperLocalMemory V3.3: The Living Brain -- Biologically-Inspired Forgetting, Cognitive Quantization, and Multi-Channel Retrieval for Zero-LLM Agent Memory Systems

Researchers have released SuperLocalMemory V3.3, an open-source AI agent memory system that operates entirely locally without cloud LLMs, implementing biologically-inspired forgetting mechanisms and multi-channel retrieval. The system achieves 70.4% performance on LoCoMo benchmarks while running on CPU only, addressing the paradox of AI agents having vast knowledge but poor conversational memory.

AIBullisharXiv – CS AI · Mar 36/109
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The Observer-Situation Lattice: A Unified Formal Basis for Perspective-Aware Cognition

Researchers introduce the Observer-Situation Lattice (OSL), a unified mathematical framework for autonomous agents to reason about multiple perspectives in complex environments. The system addresses limitations in current AI approaches by providing a single coherent structure for belief management and Theory of Mind reasoning.

AIBullisharXiv – CS AI · Mar 36/109
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GAM-RAG: Gain-Adaptive Memory for Evolving Retrieval in Retrieval-Augmented Generation

Researchers introduce GAM-RAG, a training-free framework that improves Retrieval-Augmented Generation by building adaptive memory from past queries instead of relying on static indices. The system uses uncertainty-aware updates inspired by cognitive neuroscience to balance stability and adaptability, achieving 3.95% better performance while reducing inference costs by 61%.

AIBullisharXiv – CS AI · Mar 36/104
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Cognitive Prosthetic: An AI-Enabled Multimodal System for Episodic Recall in Knowledge Work

Researchers have developed the Cognitive Prosthetic Multimodal System (CPMS), an AI-enabled proof-of-concept that helps knowledge workers recall workplace experiences by capturing speech, physiological signals, and gaze behavior into queryable episodic memories. The system processes data locally for privacy and allows natural language queries to retrieve past workplace interactions based on semantic content, time, attention, or physiological state.

AINeutralarXiv – CS AI · Mar 36/104
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From Efficiency to Adaptivity: A Deeper Look at Adaptive Reasoning in Large Language Models

Researchers present a new framework for adaptive reasoning in large language models, addressing the problem that current LLMs use uniform reasoning strategies regardless of task complexity. The survey formalizes adaptive reasoning as a control-augmented policy optimization problem and proposes a taxonomy of training-based and training-free approaches to achieve more efficient reasoning allocation.